Di He
Di He
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Cited by
Cited by
Dual learning for machine translation
D He, Y Xia, T Qin, L Wang, N Yu, TY Liu, WY Ma
Advances in neural information processing systems 29, 2016
Do Transformers Really Perform Bad for Graph Representation?
C Ying, T Cai, S Luo, S Zheng, G Ke, D He, Y Shen, TY Liu
NeurIPS 2021, 2021
A theoretical analysis of NDCG ranking measures
Y Wang, L Wang, Y Li, D He, W Chen, TY Liu
Proceedings of the 26th Annual Conference on Learning Theory (COLT 2013) 8, 6, 2013
On layer normalization in the transformer architecture
R Xiong, Y Yang, D He, K Zheng, S Zheng, C Xing, H Zhang, Y Lan, ...
International Conference on Machine Learning, 10524-10533, 2020
Incorporating bert into neural machine translation
J Zhu, Y Xia, L Wu, D He, T Qin, W Zhou, H Li, TY Liu
ICLR 2020, 2020
Multilingual neural machine translation with knowledge distillation
X Tan, Y Ren, D He, T Qin, Z Zhao, TY Liu
arXiv preprint arXiv:1902.10461, 2019
Rethinking positional encoding in language pre-training
G Ke, D He, TY Liu
arXiv preprint arXiv:2006.15595, 2020
Invertible image rescaling
M Xiao, S Zheng, C Liu, Y Wang, D He, G Ke, J Bian, Z Lin, TY Liu
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Representation degeneration problem in training natural language generation models
J Gao, D He, X Tan, T Qin, L Wang, T Liu
ICLR 2019, 2018
Frage: Frequency-agnostic word representation
C Gong, D He, X Tan, T Qin, L Wang, TY Liu
Advances in Neural Information Processing Systems, 1334-1345, 2018
Macer: Attack-free and scalable robust training via maximizing certified radius
R Zhai, C Dan, D He, H Zhang, B Gong, P Ravikumar, CJ Hsieh, L Wang
arXiv preprint arXiv:2001.02378, 2020
Non-autoregressive machine translation with auxiliary regularization
Y Wang, F Tian, D He, T Qin, CX Zhai, TY Liu
AAAI 2019, 2019
Understanding and improving transformer from a multi-particle dynamic system point of view
Y Lu, Z Li, D He, Z Sun, B Dong, T Qin, L Wang, TY Liu
arXiv preprint arXiv:1906.02762, 2019
Adversarially robust generalization just requires more unlabeled data
R Zhai, T Cai, D He, C Dan, K He, J Hopcroft, L Wang
arXiv preprint arXiv:1906.00555, 2019
Layer-wise coordination between encoder and decoder for neural machine translation
T He, X Tan, Y Xia, D He, T Qin, Z Chen, TY Liu
Advances in Neural Information Processing Systems 31, 2018
Non-autoregressive neural machine translation with enhanced decoder input
J Guo, X Tan, D He, T Qin, L Xu, TY Liu
Proceedings of the AAAI conference on artificial intelligence 33 (01), 3723-3730, 2019
Graphnorm: A principled approach to accelerating graph neural network training
T Cai, S Luo, K Xu, D He, T Liu, L Wang
International Conference on Machine Learning, 1204-1215, 2021
Efficient training of BERT by progressively stacking
L Gong, D He, Z Li, T Qin, L Wang, T Liu
International conference on machine learning, 2337-2346, 2019
Towards a deep and unified understanding of deep neural models in nlp
C Guan, X Wang, Q Zhang, R Chen, D He, X Xie
International conference on machine learning, 2454-2463, 2019
Fast structured decoding for sequence models
Z Sun, Z Li, H Wang, D He, Z Lin, Z Deng
Advances in Neural Information Processing Systems 32, 2019
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